DSP Noise Removal Project

Introduction

This repository contains a mini project for Digital Signal Processing (DSP), focused on noise removal from audio signals. The project demonstrates practical DSP techniques for enhancing speech quality by reducing unwanted noise, using Python and standard signal processing libraries.

Objectives

• Simulate and analyze noisy speech signals
• Design and implement digital filters for noise reduction
• Visualize and compare results in time and frequency domains
• Provide clear documentation and reproducible results for educational purposes

Features

• Generation of synthetic noisy speech samples
• Application of digital filtering techniques
• Visualization of time-domain and frequency-domain responses
• Comparison of original, noisy, and filtered audio samples

Project Structure

DSP_Noise_Removal_Project/
├── create_noisy_speech.py                # Script to generate noisy speech
├── main.py                              # Main script for noise removal and analysis
├── noise_removal_dsp.py                 # DSP functions and filter implementations
├── human_with_disturbance.wav           # Noisy speech sample
├── human_with_disturbance_clean.wav     # Clean speech sample
├── human_without_disturbance.wav        # Speech without disturbance
├── noisy_voice.wav                      # Additional noisy sample
├── filtered_voice.wav                   # Output after filtering
├── filter_analysis.png                  # Filter analysis plot
├── frequency_response_plot.png          # Frequency response plot
├── time_domain_plot.png                 # Time domain plot

Setup Instructions

1. Clone the repository:

   git clone https://github.com/yourusername/DSP_Noise_Removal_Project.git
   cd DSP_Noise_Removal_Project

2. Install required Python packages:

   pip install numpy scipy matplotlib

Usage Guide

• Generate noisy speech:

  python create_noisy_speech.py

• Run noise removal and analysis:

  python main.py

Results & Visualizations

Time Domain Analysis

Frequency Response

Filter Analysis

Audio Samples

• Original Clean Speech
• Noisy Speech
• Filtered Speech

Educational Value

This mini project is designed for students and enthusiasts of Digital Signal Processing. It provides hands-on experience with:

• Signal simulation and manipulation
• Filter design and evaluation
• Visualization and interpretation of DSP results

Credits

• Developed by [Your Name]
• Based on standard DSP techniques and literature

License

This project is licensed under the MIT License.

-DSP-Noise-Removal-Project